Conceptualizing Object Memory

Here we outline four distinct models to implementing memory within a dynamic system of interacting Objects. Each model provides a different mechanism for how the past influences the present, leading to unique emergent behaviors.

1. The Event Ledger Model (Memory as a Diary)

This model treats memory as a perfect, high-fidelity recording of an Object’s entire history.

• Core Concept: Memory is a complete, timestamped, and sequential log of all significant interactions an Object has experienced.
• Analogy: A ship’s log, a personal diary, or a distributed ledger like a blockchain. Each entry is an immutable record of a past event.
• Mechanism: Every Object maintains its own private “ledger,” which is a linked list of its past events. When making a decision, the Object’s internal Function can query this ledger to find specific past events, analyze sequences, and determine causality.
• Emergent Behavior: This model excels at creating subjective experience and explicit recall. It allows an Object to trace its current state back to specific historical events, leading to complex behaviors based on grudges, loyalty, or specific past promises.

2. The State-Based Model (Memory as Deformation)

In this model, memory isn’t a separate record to be read; it is physically integrated into the very being of the Object.

• Core Concept: The past is not remembered, it is embodied. An Object’s core properties are permanently altered by the Forces it encounters.
• Analogy: A piece of metal being forged. Its final shape is the memory of every hammer blow it has received. You don’t need a log of the blows to see that the metal is bent—the bend is the memory. This is also known as hysteresis.
• Mechanism: A Force acting upon an Object causes a permanent or semi-permanent change to its internal attributes (e.g., resilience, aggression, energy_level). The Object’s memory is simply its current, cumulative state.
• Emergent Behavior: This is ideal for modeling instinct, trauma, and physical conditioning. An Object can become “brittle” or “resilient” over time based on its experiences, without needing to consciously recall why. Its reactions become ingrained and instinctual.

3. The Statistical Model (Memory as Probability)

This approach treats memory as a set of learned beliefs and expectations about the world, which are constantly being updated.

• Core Concept: Memory is a statistical map of expected outcomes for various interactions, not a perfect recording of what happened.
• Analogy: Bayesian inference or a machine learning model. An AI learns to play a game by building a probabilistic model of which moves lead to good outcomes, rather than memorizing every game it has ever played.
• Mechanism: An Object maintains a distribution of probabilities for the outcomes of potential interactions (e.g., “Interacting with Object_X using Force_Y has a 70% chance of a positive result”). Each new interaction updates these probabilities.
• Emergent Behavior: This model is excellent for learning and adaptation in an uncertain environment. It allows Objects to form beliefs, recognize patterns, and make sophisticated predictions based on incomplete or noisy information.

4. The Relational Model (Memory as Connection)

In this final model, memory is not a property of any single Object, but rather an emergent feature of the entire system.

• Core Concept: Memory is stored externally, in the dynamic strength and quality of the Relationships between Objects.
• Analogy: A biological neural network. Memory and learned skills are not located in a single neuron, but are encoded in the synaptic strengths of the connections between millions of them. “Neurons that fire together, wire together.”
• Mechanism: Every Relationship link between two Objects has a dynamic weight or strength. Positive interactions strengthen this bond, while negative interactions weaken it. Memory is the overall topology of this weighted network.
• Emergent Behavior: This is the best model for observing the formation of large-scale social structures. It naturally gives rise to concepts like trust, reputation, alliances, and tribalism as emergent properties of the system’s collective memory.

Comparative Summary